Model drift
How often should you re-evaluate a model in production?
Run a fast subset on every deploy, the full suite nightly, and a human-reviewed sample of production traffic weekly. Anything slower than daily and you will hear about regressions from users first. The nightly run matters most because it catches provider-side changes that no deploy of yours would trigger.
The weekly human sample is the part teams drop, and it is the one that catches failures the rubric never anticipated — a tone problem, a new category of request, a subtly wrong answer that scores well on groundedness.
Attach the eval score to a dashboard next to latency and error rate. Quality that lives in a separate tool nobody opens is quality that is not being managed.
Ready when you are.
Tell us one thing your business does by hand today. In two weeks, we’ll show you how superintelligence would do it.
Not sure yet? Take the 3-minute readiness check, or write to growth@binaryailabs.com